{"id":"W2945220086","doi":"10.1016/j.cliser.2019.05.001","title":"Harnessing diverse knowledge and belief systems to adapt to climate change in semi-arid rural Africa","year":2019,"lang":"en","type":"article","venue":"Climate Services","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Science and Technology, Ministry of Science and Technology, India; International Development Research Centre; Department for International Development; Department of Science and Technology, Republic of the Philippines; Department for International Development, UK Government; Government of the United Kingdom","keywords":"Adaptation (eye); Arid; Climate change; Environmental resource management; Scale (ratio); Geography; Perception; Environmental science; Psychology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002087417,0.0001891097,0.0001574816,0.000825881,0.00197736,0.002106561,0.0004439004,0.0005514186,0.001026113],"category_scores_gemma":[0.004246728,0.0002245048,0.0001044441,0.000548456,0.003388187,0.001412112,0.002284834,0.0007161771,0.00006820443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152451,"about_ca_system_score_gemma":0.001130011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005915795,"about_ca_topic_score_gemma":0.0112118,"domain_scores_codex":[0.998971,0.0006404391,0.000033783,0.00005946701,0.0001075134,0.0001877459],"domain_scores_gemma":[0.9979463,0.001152066,0.000423376,0.0001135518,0.0001328173,0.0002318534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00008525373,0.0002009165,0.1349345,0.0001873636,0.00004431975,0.003426666,0.7830011,0.0003690149,0.008541414,0.005210186,0.00030973,0.06368951],"study_design_scores_gemma":[0.00002764648,0.000248507,0.1275205,0.0002749888,0.0000304259,0.001045219,0.8499994,0.001243085,0.0007432106,0.006719333,0.01210798,0.00003979309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962078,0.00009429152,0.0004039192,0.0005112605,0.000002654421,0.00001484112,0.000003653782,0.000001621289,0.002759898],"genre_scores_gemma":[0.9994936,0.00007765266,0.0002252262,0.00003877447,7.553858e-7,0.000003497659,0.000001901394,4.279322e-7,0.000158245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005915795,"threshold_uncertainty_score":0.01176274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03648248880721816,"score_gpt":0.2603612013375693,"score_spread":0.2238787125303512,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}